Development of a thermal and electrical energy management in residential building micro-grid

Abstract

Global warming and pressing concern about CO2 emission along with increasing fuel and oil cost have brought about great challenges for energy companies and homeowners. In this regard, a potential candidate solution is widely used for Distributed Energy Resources, which are capable of providing high quality, low-cost heat and power to off-grid or remote facilities. To appropriately manage thermal and electrical energy, a Smart Energy Management System (SEMS) with hierarchical control scheme has been presented. The developed SEMS model results in mixed integer non-linear programming optimization problem with the objective function of minimizing the operation cost as well as considering emissions. Moreover, the optimization problem has been solved for deterministic and stochastic scheduling algorithms. The novelty of this work is basically reliant on using data mining approach to reduce forecasting error. Several case studies have been carried out to evaluate the performance of proposed data mining method on both energy cost and expected cost.